(Digital Presentation) Elucidation of Active Oxygen Sites upon Delithiation of Li<sub>3</sub>IrO<sub>4</sub>
Bibliographic record
Abstract
Transformational increases in the storage capacity of battery cathodes could be achieved by tapping into the redox activity at oxide ligands in addition to conventional transition metal couples. Yet the key signatures that govern such lattice oxygen redox (LOR) have not been ascertained. Li3IrO4 has the largest reversible LOR, rendering it a unique model system. Here, X-ray spectroscopy and computational simulations reveal that LOR in Li3IrO4 is selectively compensated via O sites with 3 lone pairs, which are activated by Li/Ir disorder. The 2-electron LOR can be reversed to regenerate the initial state without unlocking competing bulk reactions observed in many other compounds. We uncover an intricate interplay between stoichiometry, O coordination and non-bonding states in LOR and pinpoint spectroscopic signatures. This interplay is indispensable to design materials with 3d metals that fulfill the promise of LOR to overcome the bottlenecks of current cathodes for future implementation in practical batteries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.362 | 0.033 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".